def parseRawData()

in bigtop-bigpetstore/bigpetstore-spark/src/main/scala/org/apache/bigpetstore/spark/etl/ETL.scala [64:104]

• 33 lines of code
• 1 McCabe index (conditional complexity)

  def parseRawData(rawRecords: RDD[String]):
      RDD[(Store, Location, Customer, Location, TransactionProduct)] = {
    val splitRecords = rawRecords.map { r =>
      val cols = r.split(",")

      val storeId = cols(0).toInt
      val storeZipcode = cols(1)
      val storeCity = cols(2)
      val storeState = cols(3)

      val storeLocation = Location(storeZipcode, storeCity, storeState)
      val store = Store(storeId, storeZipcode)

      val customerId = cols(4).toInt
      val firstName = cols(5)
      val lastName = cols(6)
      val customerZipcode = cols(7)
      val customerCity = cols(8)
      val customerState = cols(9)

      val customerLocation = Location(customerZipcode, customerCity,
        customerState)
      val customer = Customer(customerId, firstName, lastName,
        customerZipcode)

      val txId = cols(10).toInt
      val df = new SimpleDateFormat("EEE MMM dd kk:mm:ss z yyyy", Locale.US)
      val txDate = df.parse(cols(11))
      val txCal = Calendar.getInstance(TimeZone.getTimeZone("America/New_York"), Locale.US)
      txCal.setTime(txDate)
      txCal.set(Calendar.MILLISECOND, 0)
      val txProduct = cols(12)

      val transaction = TransactionProduct(customerId, txId,
        storeId, txCal, txProduct)

      (store, storeLocation, customer, customerLocation, transaction)
    }

    splitRecords
  }